Title:
THE PREDICTIVE MODELING OF THE FINANCIAL RISK OF CRYPTOCURRENCIES

Authors:
Mădălina CUC, Florentina-Raluca BÎLCAN, Romania

Abstract:

As the bitcoin community has grown rapidly, volatility is the only parameter that determines the price of a bitcoin and is not directly observable on the market. In this research, we apply a model of intelligent agent-based system to predict the trading price of bitcoins using data from listed cryptocurrencies like bitcoins on the CoinMarketCap. The main contribution of this paper is to show empirically that the price prediction model for bitcoins based on neural networks and the volatility prediction model based on technical analysis, form a decision support subsystem. The positive aspects of decentralization, anonymity, transparency, transaction speed and low costs, clearly show why Bitcoin is becoming more popular and future plans include generating similar bridges for other blockchains, such as Tron, EOS or Binance Chain.